1. Technical Field
This disclosure generally relates to database systems, and more specifically relates to ways of speeding up commitment control in an in-memory database in a parallel computer system.
2. Background Art
Database systems have been developed that allow a computer to store a large amount of information in a way that allows a user to search for and retrieve specific information in the database. For example, an insurance company may have a database that includes all of its policy holders and their current account information, including payment history, premium amount, policy number, policy type, exclusions to coverage, etc. A database system allows the insurance company to retrieve the account information for a single policy holder among the thousands and perhaps millions of policy holders in its database.
Some computer systems provide a large number of compute nodes that function in parallel. IBM has developed such parallel computer systems. One is known as BlueGene, another is known as Roadrunner. Parallel computer systems may have a large number of nodes, each with its own processor and memory. This characteristic provides the opportunity to provide an in-memory database, where some portions of the database, or the entire database resides completely in memory. An in-memory database provides an extremely fast response time for searches or queries of the database when all works as expected.
Database tables may be split up and distributed across several nodes in an in-memory database in a parallel computer system. If one of the nodes that contains information that is needed for a transaction stops working or becomes so busy that its latency becomes excessive, the performance of processing transactions on the in-memory database can be severely reduced. In essence, the slowest node that contains needed information becomes the bottleneck that limits the speed of the transaction. Without a way to speed up the performance of commitment control in an in-memory database, prior art parallel computer systems with in-memory databases will continue to be plagued by the bottleneck described above.